# Nfl Data Collector (`syntellect_ai/nfl-data-collector`) Actor

NFL Data Collector system with complete integration for Apify Actor and MCP server all the stats you will ever need

- **URL**: https://apify.com/syntellect\_ai/nfl-data-collector.md
- **Developed by:** [christopher athans crow](https://apify.com/syntellect_ai) (community)
- **Categories:** MCP servers, News, Developer tools
- **Stats:** 13 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.09 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## NFL Data Collector

Comprehensive NFL data collection actor for athletes, games, live scores, and fantasy football statistics from ESPN APIs.

### Features

- **Athlete Data**: Collect player information, stats, positions, teams
- **Game Data**: Past, current, and upcoming NFL games with scores
- **Live Scores**: Real-time game tracking and updates
- **Fantasy Football**: Fantasy stats with multiple data views
- **Multiple Exports**: JSON and CSV output formats
- **AI Agent Ready**: Compatible with Claude and Gemini via MCP

### Input Parameters

- **Data Types**: Select which data to collect (athletes, events, fantasy, live)
- **Limits**: Control how much data to collect for each type
- **Season**: Specify NFL season year
- **Fantasy Views**: Choose fantasy data views
- **Export Formats**: JSON and/or CSV

### Output

The actor outputs structured NFL data to the dataset with:

- Athletes with positions, teams, and stats
- Events with scores, status, and details
- Fantasy player data with decoded statistics
- Metadata about the collection

### Use Cases

- Sports analytics and predictions
- Fantasy football platforms
- Live game tracking
- Data science research
- AI agent data access

### Example Usage

```javascript
const input = {
    dataTypes: ['athletes', 'events', 'fantasy'],
    athletesLimit: 1000,
    eventsLimit: 500,
    fantasyLimit: 2000,
    season: 2024,
    exportFormats: ['json', 'csv']
};
```

### Documentation

For detailed documentation, visit the GitHub repository or check the integration guide for AI agent usage.

### License

MIT License - See repository for details

## Actor input object example

```json
{}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("syntellect_ai/nfl-data-collector").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("syntellect_ai/nfl-data-collector").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call syntellect_ai/nfl-data-collector --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,syntellect_ai/nfl-data-collector"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ZwltRhWnZ6mfyX3hg/builds/72vXsR5QPUIMOb4Y8/openapi.json